City Research Online

Abstract

A wide range of recent man-made and natural disasters has demonstrated the importance of managing disruption risk in global supply chains. This research argues that supply chain disruptions are, de facto, unavoidable and consequently all complex supply chains can be considered inherently risky. This research focuses on a relatively unexplored issue in supply chain risk management, asking and answering the question of how companies specifically use time to respond to catastrophic events of low probability but high impact. Linking faster response lead-time with reduced impact, the goal is to identify and explore the underlying factors of managing disruption risk by answering how companies respond to supply chain disruptions. In reducing total response time by detecting the event, designing solutions, and deploying a recovery plan sooner after a disruption, the company can reduce the impact of disruption risk.

The research uses Grounded Theory methodology to extend an emerging framework on time-based supply chain risk management. Empirical data is used from a range of sources including interviews and corporate publications from the events faced by global pharmaceutical manufacturer during a pandemic in 2009. The emerging categories of possible factors in response time are further developed using data from the events surrounding the worst maritime oil spill in history in 2010 under the management responsibility of the Exploration and Production (Upstream) division of a global energy company and from an industrial accident in 2005 in the Refining and Marketing division of the same firm.

The research identifies four categories of factors that companies can focus on to reduce response time in the face of catastrophic events of low probability and high impact: organisational structure, preparation, partnership and reserve. The research derives new insights, presented as four propositions that relate the response time in managing supply chain disruption to negative or potentially positive impact.

Publication Type:	Thesis (Doctoral)
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Departments:	Bayes Business School > Management Doctoral Theses Bayes Business School > Bayes Business School Doctoral Theses

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